dc dc buck converter for Model predictive control
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I have designed a dc dc buck converter for the Model predictive control, but when I run the code give the right numrical output but hte graphs are not acuret, any budy can help me to fix this problem
thank you
2 Kommentare
Chandrakanth Pavanaskar
am 13 Jul. 2022
Hello,
I just saw your model, can I know how did you get the solution as the solution seems infeasible
Sam Chak
am 13 Jul. 2022
I'm unsure, but from the mathematical perspective, the system looks 'manipulatable' with numbers without using MPC. What is the purpose of having the MPC in this case?
Vg = 15; D = 0.4; L = 2e-3; C = 10e-6; R = 100;
a = [0 -(1-D)/L; (1-D)/C -1/(R*C)];
b = [1/L 0; 0 -1/C];
c = eye(length(a));
d = [0];
sys = ss(a, b, c, d); % System in state-space model
k1 = 1;
k2 = 1;
k = [-k1/500 3/5; 0.6 (k2 - 1e3)/1e5] % Gain Matrix
br = diag([k1/500, -k2/1e5])*b; % Rescaled Reference Input Matrix
CLsys = ss(a+b*k, br, c, d) % Closed-loop system
step(CLsys) % Closed-loop step response
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Chandrakanth Pavanaskar
am 14 Jul. 2022
Hello,
Can I know the research material for this MPC design of buck converter?
Thank you
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